Analysis and control of quality of information (QoI) for wireless sensor networks

2015 ◽  
Vol 8 (2) ◽  
pp. 103
Author(s):  
Shensheng Tang ◽  
Brenten Davis
2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Hao Guo ◽  
Zhongming Pan ◽  
Zhiping Huang ◽  
Jing Zhou

As wireless sensor networks (WSNs) often provide incorrect and outdated information about the events in a monitored environment, quality of information (QoI) assessment is invaluable for users to manage and use the information in particular applications. In this paper, we propose a flexible framework to dynamically assess the QoI in different WSN applications, with focus on accuracy and timeliness. Our framework is constructed on the infrastructure of an information aggregation procedure under some assumptions about the network. Based on information fusion theory, two processing models are adopted to assess the accuracy of low-level measurement data and high-level decision information without the need for Ground Truth (GT). Meanwhile, our framework generally exploits two respective models according to the specific category of the information timeliness in different delay-sensitive applications. To quantify the timeliness, we utilize a practical measurement method by means of timestamp to determine the information acquisition time. The framework is evaluated by simulations, including accuracy assessment in two environmental monitoring application scenarios, and timeliness assessment in two delay-sensitive application scenarios. The simulation results show that our framework is effective and flexible for quantitative assessment of the QoI in different WSN applications.


2016 ◽  
Vol 10 (17) ◽  
pp. 2281-2289 ◽  
Author(s):  
Pengfei Du ◽  
Qinghai Yang ◽  
Qingsu He ◽  
Kyung Sup Kwak

2016 ◽  
Vol 16 (19) ◽  
pp. 7278-7286 ◽  
Author(s):  
Pengfei Du ◽  
Qinghai Yang ◽  
Zhong Shen ◽  
Kyung Sup Kwak

In India 60 percent of total cultivated land is fully dependent on rain and if there is less than average rain fall than it results into significant reduction in the overall agricultural production and it leads heavy losses to farmers and ultimately it affects the overall gross domestic production of India. Banana is an important fruit and it is one of good cash crop in India. In this research work, our aim is to design and implement Banana Crop System (Banntex) to sense crucial parameters and early detection of diseases and control using Wireless Sensor Networks (WSN) and Internet of Things (IoT). To implement Banntex we uses advancement of new technology like Internet of Things (IoT), Sensors development and Improved Wireless Sensor Networks, we can design and developed Precision Agriculture systems in which various sensors are used to measure the different parameters like temperature of air and soil, relative humidity, water potential of banana field, pH value of soil, Electric conductivity of soil, salinity of banana field soil, Moisture changes in soil, soil quality, fertility of soil, ground water quality and crop growth. Based on the measured parameters this system can be used to control and automate the farming processes. This precision system empowers farmers to keep updated, early detection of soil parameters and take necessary steps to improve it further. It results to improve the biomass, roots and overall growth of banana crops and finally it increases productivity and improved quality of farming with minimum manual tasks. Experimental results will show the significant improvement in the Banana crop production and Quality of Banana Fruit using our proposed Banntex System.


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